Add HUB-SDK docs (#7775)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>

.github/workflows/publish.yml

@@ -66,7 +66,6 @@ jobs:
         env:
           PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
           INDEXNOW_KEY: ${{ secrets.INDEXNOW_KEY_DOCS }}
-          WEGLOT_KEY: ${{ secrets.WEGLOT_KEY_DOCS }}
         run: |
           python docs/build_docs.py
           git config --global user.name "Glenn Jocher"

docs/build_docs.py

@@ -33,24 +33,36 @@ from tqdm import tqdm
 
 DOCS = Path(__file__).parent.resolve()
 SITE = DOCS.parent / "site"
-LANGUAGES = False
 
 
-def build_docs():
+def build_docs(use_languages=False, clone_repos=True):
     """Build docs using mkdocs."""
     if SITE.exists():
         print(f"Removing existing {SITE}")
         shutil.rmtree(SITE)
 
+    # Get hub-sdk repo
+    if clone_repos:
+        repo = "https://github.com/ultralytics/hub-sdk"
+        local_dir = DOCS.parent / Path(repo).name
+        if not local_dir.exists():
+            os.system(f"git clone {repo} {local_dir}")
+        os.system(f"git -C {local_dir} pull")  # update repo
+        shutil.rmtree(DOCS / "en/hub/sdk")
+        shutil.copytree(local_dir / "docs", DOCS / "en/hub/sdk")
+        shutil.rmtree(DOCS / "en/hub/sdk/reference")  # temporarily delete reference until we find a solution for this
+        print(f"Cloned/Updated {repo} in {local_dir}")
+
     # Build the main documentation
     print(f"Building docs from {DOCS}")
     subprocess.run(f"mkdocs build -f {DOCS}/mkdocs.yml", check=True, shell=True)
 
     # Build other localized documentations
-    if LANGUAGES:
+    if use_languages:
         for file in DOCS.glob("mkdocs_*.yml"):
             print(f"Building MkDocs site with configuration file: {file}")
             subprocess.run(f"mkdocs build -f {file}", check=True, shell=True)
+        update_html_links()  # update .md in href links
     print(f"Site built at {SITE}")
 
 
@@ -104,21 +116,13 @@ def update_page_title(file_path: Path, new_title: str):
         file.write(updated_content)
 
 
-def update_html_head(key=""):
+def update_html_head(script=""):
     """Update the HTML head section of each file."""
     html_files = Path(SITE).rglob("*.html")
     for html_file in tqdm(html_files, desc="Processing HTML files"):
         with html_file.open("r", encoding="utf-8") as file:
             html_content = file.read()
 
-        script = f"""
-<script type="text/javascript" src="https://cdn.weglot.com/weglot.min.js"></script>
-<script>
-    Weglot.initialize({{
-        api_key: '{key}'
-    }});
-</script>
-"""
         if script in html_content:  # script already in HTML file
             return
 
@@ -137,13 +141,8 @@ def main():
     # Update titles
     update_page_title(SITE / "404.html", new_title="Ultralytics Docs - Not Found")
 
-    # Update .md in href links
-    if LANGUAGES:
-        update_html_links()
-
     # Update HTML file head section
-    if not LANGUAGES and False:
+    # update_html_head("")
-        update_html_head(key=os.environ.get("WEGLOT_KEY"))
 
     # Show command to serve built website
     print('Serve site at http://localhost:8000 with "python -m http.server --directory site"')

docs/coming_soon_template.md

@@ -0,0 +1,34 @@
+---
+description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
+keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
+---
+
+# Under Construction 🏗️🌟
+
+Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
+
+## Exciting New Features on the Way 🎉
+
+- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
+- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
+- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
+
+## Stay Updated 🚧
+
+This placeholder page is your first stop for upcoming developments. Keep an eye out for:
+
+- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
+- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
+- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
+
+## We Value Your Input 🗣️
+
+Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
+
+## Thank You, Community! 🌍
+
+Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
+
+---
+
+Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖

docs/en/hub/api/index.md

@@ -0,0 +1,34 @@
+---
+description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
+keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
+---
+
+# Under Construction 🏗️🌟
+
+Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
+
+## Exciting New Features on the Way 🎉
+
+- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
+- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
+- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
+
+## Stay Updated 🚧
+
+This placeholder page is your first stop for upcoming developments. Keep an eye out for:
+
+- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
+- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
+- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
+
+## We Value Your Input 🗣️
+
+Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
+
+## Thank You, Community! 🌍
+
+Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
+
+---
+
+Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖

docs/en/hub/index.md

@@ -58,4 +58,4 @@ We hope that the resources here will help you get the most out of HUB. Please br
 - [**Ultralytics HUB App**](app/index.md). Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
     - [**iOS**](app/ios.md). Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
     - [**Android**](app/android.md). Explore TFLite acceleration on mobile devices.
-- [**Inference API**](inference_api.md). Understand how to use the Inference API for running your trained models in the cloud to generate predictions.
+- [**Inference API**](inference-api.md). Understand how to use the Inference API for running your trained models in the cloud to generate predictions.

docs/en/hub/inference-api.md

@@ -103,7 +103,7 @@ The JSON list contains information about the detected objects, their coordinates
 
 ### Detect Model Format
 
-YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
+YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
 
 !!! Example "Detect Model JSON Response"
 
@@ -122,7 +122,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
         print(results[0].tojson())
         ```
 
-    === "CLI API"
+    === "CLI"
 
         ```bash
         curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@@ -133,7 +133,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
             -F "iou=0.45"
         ```
 
-    === "Python API"
+    === "Python"
 
         ```python
         import requests
@@ -201,7 +201,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
 
 ### Segment Model Format
 
-YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
+YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
 
 !!! Example "Segment Model JSON Response"
 
@@ -220,7 +220,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
         print(results[0].tojson())
         ```
 
-    === "CLI API"
+    === "CLI"
 
         ```bash
         curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@@ -231,7 +231,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
             -F "iou=0.45"
         ```
 
-    === "Python API"
+    === "Python"
 
         ```python
         import requests
@@ -342,7 +342,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
 
 ### Pose Model Format
 
-YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, CLI API inference, and Python API inference. All of these methods produce the same JSON response format.
+YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
 
 !!! Example "Pose Model JSON Response"
 
@@ -361,7 +361,7 @@ YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from loca
         print(results[0].tojson())
         ```
 
-    === "CLI API"
+    === "CLI"
 
         ```bash
         curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@@ -372,7 +372,7 @@ YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from loca
             -F "iou=0.45"
         ```
 
-    === "Python API"
+    === "Python"
 
         ```python
         import requests

docs/en/hub/models.md

@@ -124,7 +124,7 @@ You can preview your model if you click on the **Preview** tab and upload an ima
 
 ![Ultralytics HUB screenshot of the Preview tab (Test card) inside the Model page](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/models/hub_preview_model_1.jpg)
 
-You can also use our Ultralytics Cloud API to effortlessly [run inference](https://docs.ultralytics.com/hub/inference_api) with your custom model.
+You can also use our Ultralytics Cloud API to effortlessly [run inference](inference-api.md) with your custom model.
 
 ![Ultralytics HUB screenshot of the Preview tab (Ultralytics Cloud API card) inside the Model page](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/models/hub_preview_model_2.jpg)
 

docs/en/hub/on-premise/index.md

@@ -0,0 +1,34 @@
+---
+description: Discover what's next for Ultralytics with our under-construction page, previewing new, groundbreaking AI and ML features coming soon.
+keywords: Ultralytics, coming soon, under construction, new features, AI updates, ML advancements, YOLO, technology preview
+---
+
+# Under Construction 🏗️🌟
+
+Welcome to the Ultralytics "Under Construction" page! Here, we're hard at work developing the next generation of AI and ML innovations. This page serves as a teaser for the exciting updates and new features we're eager to share with you!
+
+## Exciting New Features on the Way 🎉
+
+- **Innovative Breakthroughs:** Get ready for advanced features and services that will transform your AI and ML experience.
+- **New Horizons:** Anticipate novel products that redefine AI and ML capabilities.
+- **Enhanced Services:** We're upgrading our services for greater efficiency and user-friendliness.
+
+## Stay Updated 🚧
+
+This placeholder page is your first stop for upcoming developments. Keep an eye out for:
+
+- **Newsletter:** Subscribe [here](https://ultralytics.com/#newsletter) for the latest news.
+- **Social Media:** Follow us [here](https://www.linkedin.com/company/ultralytics) for updates and teasers.
+- **Blog:** Visit our [blog](https://ultralytics.com/blog) for detailed insights.
+
+## We Value Your Input 🗣️
+
+Your feedback shapes our future releases. Share your thoughts and suggestions [here](https://ultralytics.com/contact).
+
+## Thank You, Community! 🌍
+
+Your [contributions](https://docs.ultralytics.com/help/contributing) inspire our continuous [innovation](https://github.com/ultralytics/ultralytics). Stay tuned for the big reveal of what's next in AI and ML at Ultralytics!
+
+---
+
+Excited for what's coming? Bookmark this page and get ready for a transformative AI and ML journey with Ultralytics! 🛠️🤖

docs/en/usage/cli.md

@@ -1,6 +1,6 @@
 ---
 comments: true
-description: Learn how to use Ultralytics YOLO through Command Line: train models, run predictions and exports models to different formats easily using terminal commands.
+description: Learn how to use Ultralytics YOLO through Command Line, train models, run predictions and exports models to different formats easily using terminal commands.
 keywords: Ultralytics, YOLO, CLI, train, validation, prediction, command line interface, YOLO CLI, YOLO terminal, model training, prediction, exporting
 ---
 

docs/mkdocs.yml

@@ -343,17 +343,28 @@ nav:
       - TensorBoard: integrations/tensorboard.md
       - Amazon SageMaker: integrations/amazon-sagemaker.md
   - HUB:
-      - hub/index.md
+      - Cloud:
-      - Quickstart: hub/quickstart.md
+          - hub/index.md
-      - Datasets: hub/datasets.md
+          - Quickstart: hub/quickstart.md
-      - Projects: hub/projects.md
+          - Datasets: hub/datasets.md
-      - Models: hub/models.md
+          - Projects: hub/projects.md
-      - Integrations: hub/integrations.md
+          - Models: hub/models.md
-      - Ultralytics HUB App:
+          - Integrations: hub/integrations.md
+          - Inference API: hub/inference-api.md
+      - On Premise:
+          - hub/on-premise/index.md
+      - App:
           - hub/app/index.md
           - iOS: hub/app/ios.md
           - Android: hub/app/android.md
-      - Inference API: hub/inference_api.md
+      - Python SDK:
+          - hub/sdk/index.md
+          - Quickstart: hub/sdk/quickstart.md
+          - Model: hub/sdk/model.md
+          - Dataset: hub/sdk/dataset.md
+          - Project: hub/sdk/project.md
+      - REST API:
+          - hub/api/index.md
 
   - Reference:
       - cfg:
@@ -542,6 +553,7 @@ plugins:
         quick-start.md: quickstart.md
         app.md: hub/app/index.md
         sdk.md: index.md
+        hub/inference_api.md: hub/inference-api.md
         usage/hyperparameter_tuning.md: integrations/ray-tune.md
         reference/base_pred.md: reference/engine/predictor.md
         reference/base_trainer.md: reference/engine/trainer.md

ultralytics/engine/model.py

@@ -259,8 +259,8 @@ class Model(nn.Module):
             x in sys.argv for x in ("predict", "track", "mode=predict", "mode=track")
         )
 
-        custom = {"conf": 0.25, "save": is_cli}  # method defaults
+        custom = {"conf": 0.25, "save": is_cli, "mode": "predict"}  # method defaults
-        args = {**self.overrides, **custom, **kwargs, "mode": "predict"}  # highest priority args on the right
+        args = {**self.overrides, **custom, **kwargs}  # highest priority args on the right
         prompts = args.pop("prompts", None)  # for SAM-type models
 
         if not self.predictor: